S4 Dataset -

<div><p>In recent years, the utilization of motor imagery (MI) signals derived from electroencephalography (EEG) has shown promising applications in controlling various devices such as wheelchairs, assistive technologies, and driverless vehicles. However, decoding EEG signals poses signi...

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محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Jaipriya D. (20571339) (author)
مؤلفون آخرون:	Sriharipriya K. C. (20571342) (author)
منشور في:	2025
الموضوعات:	Physiology Biotechnology Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified transfer learning technique specifically datasets 2a shown promising applications employ confusion matrices empirical mode decomposition controlling various devices bci competition iv various performance metrics improve performance speed enhance classification accuracy enhanced performance feature classification classification accuracy classification accuracies xlink "> stationary issues snr ). signals derived results demonstrate recent years quantitative analyses noise ratio motor imagery mitigate non low signal individual subjects identifying two high accuracy group dataset findings highlight feature extraction existing approaches dynamic nature driverless vehicles broader applicability assistive technologies approach aims accurate operation
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S4 Dataset -

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